Modeling And Dynamic Analysis of Factors Affecting Data Quality of University Portal with an Integrated Approach of System Dynamics and Quality Function (Case Study: Amirkabir University of Technology)

Subject Areas : Strategic Management Researches

Maedeh  Alizadeh ¹ (PhD Candidate, Department of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran)
Mohammad Reza  Motadel ² (Assistant Professor, Department of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran)
Navid  Nezafati ³ (Assistant Professor, Management and accounting, Shahid Beheshti University, Tehran, Iran)

Received: 2023-01-01 Accepted : 2023-02-02 Published : 2023-02-20

Keywords: System Dynamics, Data Quality Dimensions, University Portal, Data Quality Model, Quality Performance Expansion,

Abstract :

The purpose of this paper is to provide data quality model of a university portal with an integrated approach of system dynamics and quality function deployment. The present study is applied in terms of descriptive – survey method research. Following paper aims to provide a model and identify the concept and its dimensions for an academic portal and through using library study methods as well as field methods such as questionnaires, content analysis methods and Fuzzy Delphi method simultaneously, collect the voices of different users regarding data quality and finally, with the formation of four quality house matrices, it led to design requirements. Based on Quality Deployment Function analysis, found out that Extensible Markup Language (XML) could be more proper programming language to achieve flexibility as one of the most important engineering characteristics to fulfill user’s requirements. The important ambiguous issue in this context was how the internal communication between the requirements was; As a result of simulating these relationships, it was found that the way of communication overshadows the whole results. At the time of planning in the field of data quality and presenting a model in this regard, it should be considered that the factors may have conflicting relationships and unilaterally addressing a requirement or characteristic without considering its relationship with other cases could have the opposite result and efforts related to it will be fruitless.

References:

رحیمی, ‌علیرضا, فرج‌پهلو, ‌عبدالحسین, عصاره, ‌فریده, و شهبازی, ‌مهری. (1396). بررسی تحولات پژوهش های حوزه ارزیابی کیفیت داده ها و اطلاعات در نظام های اطلاعاتی از سال 2000 تا نیمۀ نخست 2015. پردازش و مدیریت اطلاعات, 90(33), 915–944

علیزاده, م., معتدل, م., و نظافتی, ن. (۱۴۰۰). مدل‌سازی سطح کیفیت داده‌های پورتال دانشگاهی با استفاده از تکنیک گسترش عملکرد کیفیت (مطالعه موردی: دانشگاه صنعتی امیرکبیر). علوم و فنون مدیریت اطلاعات, 7(4), 15–46. doi:10.22091/stim.2020.5917.1434

Moossavizadeh, S. M. H. & Mohsenzadeh, M. & Arshadi, N. (2012). A new approach to measure believability dimension of data quality. Management Science Letters, 2, 2565-2570. https://doi.org/10.5267/j.msl.2012.07.007

Dania, W. A. P. & Xing, K. & Amer, Y. (2019). Collaboration quality assessment for sustainable supply chains: benchmarking. Benchmarking: An International Journal, 26. https://doi.org/10.1108/BIJ-03-2018-0070

Shaker, F. & Shahin, A. & Jahanyan, S. (2019). Developing a two-phase QFD for improving FMEA: an integrative approach. International Journal of Quality & Reliability Management, 36. https://doi.org/10.1108/IJQRM-07-2018-0195

Moğol Sever, M. (2018). Improving check-in (C/I) process: an application of the quality function deployment. International Journal of Quality & Reliability Management, 35(9), 1907-1919. https://doi.org/10.1108/IJQRM-03-2017-0043

Erdil, N. O. & Arani, O. (2018). Quality function deployment: more than a design tool. International Journal of Quality and Service Sciences, 11. https://doi.org/10.1108/IJQSS-02-2018-0008

Gangurde, S. & Patil, S. (2018). Benchmark product features using Kano - QFD approach: a case study. Benchmarking: An International Journal, 25, 00-00. https://doi.org/10.1108/BIJ-08-2016-0131

Vetro, A. & Canova, L. & Torchiano, M. & Minotas, C. Iemma, R. & Morando, F. (2016). Open data quality measurement framework: Definition and application to Open Government Data. Government Information Quarterly, 33. https://doi.org/10.1016/j.giq.2016.02.001

Chen, L.H. & Chen, C.N. (2014). Normalisation models for prioritising design requirements for quality function deployment processes. International Journal of Production Research, 52(2), 299-313. https://doi.org/10.1080/00207543.2013.812813

Kwon, O. Lee, N. & Shin, B. (2014). Data quality management, data usage experience and acquisition intention of big data analytics. International Journal of Information Management, 34(3), 387-394. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2014.02.002

Raissi, S. Izadi, M. & Saati, S. (2012). Prioritizing Engineering Characteristics in QFD Using Fuzzy Common Set of Weight Method. American Journal of Scientific Research, 49, 34-49.

Rafique, I. Lew, P. Abbasi, M. Q. & Li, Z. (2012). Information quality evaluation framework: Extending ISO 25012 data quality model. World academy of science. Engineering and Technology, 65, 523-528.

Rahimi, A. Farajpahlou, H. Osareh, F. & Shahbazi, M. (2018). Developments of research in evaluation of data and information quality in information systems since the year. IranDoc, 33(2), 915-944. http://jipm.irandoc.ac.ir/article-1-3323-fa.html

Strong, D. Lee, Y. & Wang, R. (2002). Data Quality in Context. Communications of the ACM, 40. https://doi.org/10.1145/253769.253804

Redman, T. (1998). The Impact of Poor Data Quality on the Typical Enterprise. Communications of the ACM, 41. https://doi.org/10.1145/269012.269025

Caro, A. Calero, C. Caballero, I. & Piattini, M. (2008). A proposal for a set of attributes relevant for Web portal data quality. Software Quality Journal, 16(4), 513-542. https://doi.org/10.1007/s11219-008-9046-7

Rajamani, S. (2005). Information Systems with Emphasis on Business Rules for Demographics: A Kaizen Strategy for Data Quality in Public Health Informatics. University of Minnesota. https://books.google.com/books?id=UOZLGwAACAAJ

Barutçu, S. (2019). Health apps design using quality function deployment. International Journal of Health Care Quality Assurance, 32(4), 698-708. https://doi.org/10.1108/IJHCQA-08-2018-0195

Camgöz-Akdağ, H. İmer, H. P. & Ergin, K. N. (2016). Internal customer satisfaction improvement with QFD technique. Business Process Management Journal, 22(5), 957-968. https://doi.org/10.1108/BPMJ-01-2016-0022

Sushil. (1993). System Dynamics: A Practical Approach for Managerial Problems. Wiley Eastern Limited. https://books.google.com/books?id=lJVYAAAAYAAJ

Assad, A. & Gass, S. (2011). Profiles in Operations Research: Pioneers and Innovators (Vol. 147). https://doi.org/10.1007/978-1-4419-6281-2

Alizadeh, M. Motadel, M. Nezafati, N. (2020). Modeling Quality Level of University Portal Data using Quality Function Deployment (QFD), Case Study: Amirkabir University of Technology. Sciences and Techniques of Information Management, doi: 10.22091/stim.2020.5917.1434

C. Cichy and S. Rass, "An Overview of Data Quality Frameworks," in IEEE Access, vol. 7, pp. 24634-24648, 2019, doi: 10.1109/ACCESS.2019.2899751.

Abhinav Jain, Hima Patel, Lokesh Nagalapatti, Nitin Gupta, Sameep Mehta, Shanmukha Guttula, Shashank Mujumdar, Shazia Afzal, Ruhi Sharma Mittal, and Vitobha Munigala. 2020. Overview and Importance of Data Quality for Machine Learning Tasks. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD '20). Association for Computing Machinery, New York, NY, USA, 3561–3562. doi: 10.1145/3394486.3406477